AMMI index and yield stability

calculate AMMI stability value (ASV) and Yield stability index (YSI).

index.AMMI(model)

Arguments

model	object AMMI

Value

ASV

AMMI stability value

YSI

Yield stability index

rASV

Rank of AMMI stability value

rYSI

Rank of yield stability index

means

average genotype by environment

Details

AMMI stability value (ASV) was calculated using the following formula, as suggested by Purchase (1997)

ASV = sqrt((SSpc1/SSpc2 * PC1i)^2+(PC2i)^2)

YSI = RASV + RY

RASV = rank(ASV) and RY = rank(Y across by environment)

References

The use of an AMMI model and its parameters to analyse yield stability in multienvironment trials. N. SABAGHNIA, S.H. SABAGHPOUR AND H. DEHGHANI. Journal of Agricultural Science (2008), 146, 571-581. f 2008 Cambridge University Press 571 doi:10.1017/S0021859608007831 Printed in the United Kingdom

Parametric analysis to describe genotype x environment interaction and yield stability in winter wheat. PURCHASE, J. L. (1997). Ph.D. Thesis, Department of Agronomy, Faculty of Agriculture of the University of the Free State, Bloemfontein, South Africa.

See also

AMMI,plot.AMMI

Examples

library(agricolae)
# Index AMMI
data(plrv)
model<- with(plrv,AMMI(Locality, Genotype, Rep, Yield, console=FALSE))
Idx<-index.AMMI(model)
names(Idx)
#> [1] "ASV"   "YSI"   "rASV"  "rYSI"  "means"
# Crops with improved stability according AMMI.
print(Idx[order(Idx[,3]),])
#>               ASV YSI rASV rYSI    means
#> 402.7   0.2801470  20    1   19 27.47748
#> 364.21  0.7236998  12    2   10 34.05974
#> 506.2   0.7511331  14    3   11 33.26623
#> 233.11  1.0582263  21    4   17 28.66655
#> 427.7   1.1467970  12    5    7 36.19020
#> 104.22  1.4627695  19    6   13 31.28887
#> 241.2   1.6774241  29    7   22 26.34039
#> 221.19  1.8014494  34    8   26 22.98480
#> 317.6   2.1874274  18    9    9 35.32583
#> 121.31  2.2937918  25   10   15 30.10174
#> 406.12  2.5631734  23   11   12 32.68323
#> 314.12  2.9170536  30   12   18 28.17335
#> 342.15  2.9219360  37   13   24 26.01336
#> 351.26  2.9786832  22   14    8 36.11581
#> Canchan 3.0975884  35   15   20 27.00126
#> 450.3   3.1430174  22   16    6 36.19602
#> 157.26  3.2923168  22   17    5 36.95181
#> 320.16  3.3208950  39   18   21 26.34808
#> 255.7   3.3289736  33   19   14 30.58975
#> 102.18  3.3801820  43   20   23 26.31947
#> 235.6   3.7647078  25   21    4 38.63477
#> Unica   3.8380782  24   22    2 39.10400
#> 405.2   3.9832546  39   23   16 28.98663
#> 163.9   4.4269636  51   24   27 21.41747
#> 141.28  4.4672401  26   25    1 39.75624
#> 346.2   5.1827747  51   26   25 23.84175
#> 319.20  6.7164864  30   27    3 38.75767
#> Desiree 7.7833445  56   28   28 16.15569
# Crops with better response and improved stability according AMMI.
print(Idx[order(Idx[,4]),])
#>               ASV YSI rASV rYSI    means
#> 141.28  4.4672401  26   25    1 39.75624
#> Unica   3.8380782  24   22    2 39.10400
#> 319.20  6.7164864  30   27    3 38.75767
#> 235.6   3.7647078  25   21    4 38.63477
#> 157.26  3.2923168  22   17    5 36.95181
#> 450.3   3.1430174  22   16    6 36.19602
#> 427.7   1.1467970  12    5    7 36.19020
#> 351.26  2.9786832  22   14    8 36.11581
#> 317.6   2.1874274  18    9    9 35.32583
#> 364.21  0.7236998  12    2   10 34.05974
#> 506.2   0.7511331  14    3   11 33.26623
#> 406.12  2.5631734  23   11   12 32.68323
#> 104.22  1.4627695  19    6   13 31.28887
#> 255.7   3.3289736  33   19   14 30.58975
#> 121.31  2.2937918  25   10   15 30.10174
#> 405.2   3.9832546  39   23   16 28.98663
#> 233.11  1.0582263  21    4   17 28.66655
#> 314.12  2.9170536  30   12   18 28.17335
#> 402.7   0.2801470  20    1   19 27.47748
#> Canchan 3.0975884  35   15   20 27.00126
#> 320.16  3.3208950  39   18   21 26.34808
#> 241.2   1.6774241  29    7   22 26.34039
#> 102.18  3.3801820  43   20   23 26.31947
#> 342.15  2.9219360  37   13   24 26.01336
#> 346.2   5.1827747  51   26   25 23.84175
#> 221.19  1.8014494  34    8   26 22.98480
#> 163.9   4.4269636  51   24   27 21.41747
#> Desiree 7.7833445  56   28   28 16.15569